Data Engineer Sql (Bi)

At least three years of experience collecting, cleaning, harmonising and analysing structured and semi-structured data using SQL and Python, R or equivalent technologies.- At least three years of experience in data extraction and transformation, the construction and maintenance of relational or analytical databases, and the preparation of reproducible datasets with metadata and data dictionaries.- At least three years of experience in entity identification, name standardisation, record linkage, deduplication, data-quality checks, validation and reconciliation across multiple heterogeneous data sources.- At least two years of experience in exploratory, descriptive or comparative data analysis, or in indicator development.- At least one year of experience using machine-learning, NLP or AI-assisted tools to process and analyse textual or other unstructured information.- At least six months of experience processing and analysing EU funding data or public-sector and administrative data sources.- At least six months of experience in data visualisation and communicating analytical findings to non-technical audiences.Technical Skills Candidates should demonstrate proficiency in several of the following technologies:- SQL- Python- R- Microsoft Power BI- Qlik- Microsoft Fabric Certifications A recognised professional certification in data analytics, business intelligence, data engineering, database management or data governance is required.Relevant certifications include:- Microsoft Certified: Power BI Data Analyst Associate- Microsoft Certified: Azure Data Engineer Associate- Microsoft Certified: Fabric Analytics Engineer Associate- Microsoft Certified: Fabric Data Engineer Associate- An equivalent recognised professional certification

At least three years of experience collecting, cleaning, harmonising and analysing structured and semi-structured data using SQL and Python, R or equivalent technologies.

• At least three years of experience in data extraction and transformation, the construction and maintenance of relational or analytical databases, and the preparation of reproducible datasets with metadata and data dictionaries.
• At least three years of experience in entity identification, name standardisation, record linkage, deduplication, data-quality checks, validation and reconciliation across multiple heterogeneous data sources.
• At least two years of experience in exploratory, descriptive or comparative data analysis, or in indicator development.
• At least one year of experience using machine-learning, NLP or AI-assisted tools to process and analyse textual or other unstructured information.
• At least six months of experience processing and analysing EU funding data or public-sector and administrative data sources.

• At least six months of experience in data visualisation and communicating analytical findings to non-technical audiences. Technical Skills Candidates should demonstrate proficiency in several of the following technologies:

• SQL
• Python
• R
• Microsoft Power BI
• Qlik
• Microsoft Fabric Certifications A recognised professional certification in data analytics, business intelligence, data engineering, database management or data governance is required., An equivalent recognised professional certification